I recently finished readingÂ Trading Realities by Jeff Augen. The book was made available to be for free (via Amazon) and I opted to give it a look because it sounded like it was written for new traders. Obviously, theÂ area of new trader education is one I have a lot of interest in. That being the case, I thought it made a lot of sense to check this book out to see if it was worth recommending.

Unfortunately, this isn’t one I’m putting on my recommended list.

I’m not entirely sure what the point of this book was. I think it was to present option trading as a better path for trading the stock market than actually trading the stocks themselves, but I can’t beÂ positive. The author does do a pretty good job of laying out some option strategies that could be used along with or in place of holding stocks, and I definitely agree that for many people they present a better path (I for one have been trading options rather than stocks forÂ quite a fewÂ years). That’s just one chapter out of seven, though.

Unclear focus aside, I have a fewÂ major issues with the book.

First, there are things he says in the book which are flat out incorrect. One of them is very early on and very obvious for anyone familiar with the currency market. He suggests that during the major dollar weakness a few years ago the Yen reached a value ofÂ $1.15. The fact of the matter is that the Yen has never been worth more than about $0.0125 – that one and a quarter cents. This isn’t a horrible error, and doesn’t alter the context of what he’s saying at that point in the text, but it does trigger a credibility warning flags.

A much bigger error, especially coming from someone claiming expertise in options, comes when he talks about price change distributions – an important element in volatility measurement and option pricing. He makes the statement “These values fit a bell-shaped curve where the peak represents a small number of unusually large price changes.” This is totally incorrect. The peak of a bell curve represents a very high frequency of small price changes. I thought maybe he’d just misspoke, but in the same paragraph the author goes on to talk about how the large price spike in Amazon was the peak of the bell curve of that stock’s price change distribution. Anyone who’s ever studied basic statistics would know that to be completely backwards. This definitely challenges his credibility.

Oh, and he talks about price changes in terms of them fitting a standard normal distribution, which has been well documented as being incorrect. Real price change distributions in the market have fatter “tails”, which mean higher probabilities of large price moves than a normal distribution would suggest.

My second issue with the book was the extreme cynicism that dominated most of the first half of the text. The author basically goes off on a rant about things like the impact of high frequency trading, how investors who think they can do a better job picking stocks are fooling themselves, and how the government is lying to us through the statistics it publishes. There are talking points in there, to be sure, but the one example of erroneousÂ stats he show is hardly proof of anything.

Another issue I have is the amount of ex post facto market analysis the author does in the text. At points it’s little more than a history lesson. Sure, there’s always value in going back and reviewing things, but isolated examples of how one should have interpreted developments doesn’t really give the reader a lot they can use moving forward – especially since, according to the author, the individual cannot hope to beat the institutions anyway.

But wait! In the latter half of the book the author lays out directionally based options strategies which imply the trader/investor is looking for the market to move a certain way and can get it right. He also talks late in the bookÂ about how modern technology allows individuals to identify inefficiencies in the market, even though he spent pages earlier talking about how the market is efficient and how individuals cannot hope to compete on the technology side with the institutions. In other words, there’s a fair bit of contradiction.

The author has other books on option trading which might be better choices. Needless to say, I’d skip this one.

I know you are a position trader in the stock market, using a variation of CANSLIM. You are a day trader in ES, using Market Profile. I think these are great ways to approach these markets. That’s why I would like to know how do you approach the Forex market:

– Are you a position trader? If so, do you scale-in or pyramid to build large size or do you difersify as much as possible?

– I know you use weekly Bollinger Bands and forex seasonals, but is that enough to time your entries or do you use other tools or analyses?

Thank you.

Rod

Before I talk about my forex trading, let me back fill a bit for those who haven’t followed my work. The strategy for the individual stock trading I do – which Rod correctly notes has CANSLIM as it’s foundation – can be found in an appendix to by book The Essentials of Trading. It is a strategy which combines technicals and fundamentals, and I figure on holding positions for 8 weeks when I put on a trade.The ES (mini S&P 500 futures) trading I do definitely utilizes a Market Profile approach, though I wouldn’t strictly call it day trading because I do sometimes carry positions overnight.

Now, as for forex, I do like being more of a position trader, holding trades for weeks or even months to catch good-sized trends. Sometimes I also play more swing time frame trades. Regardless of the time frame, though, my approach is basically the same. I use the Bollingers to find situations where a new trend looks likely to develop, pretty straightforward chart analysis to identify entry and exit points, and the attractor ideas from Market Profile to identify likely target points.

As for the forex seasonals, I use those to bias or filter my trading, especially the more swing oriented positions. For example, if a pair I like to trade is biased higher in September I’ll look for good long entry opportunities. I’m also planning some research into more mechanical strategies there.

In terms of scaling in and things of that nature, my history has been mixed. I’ve definitely had some times where I’ve added to positions as a trend unfolded in my direction. Other times I’ve just gone the all-in route from the start. I’m not a diversifier specifically. I do look to avoid getting overweight in any specific risk area (like being too long or short a particular currency), but because I tend to focus on one position, or at most a small number of them, at a time it really isn’t an issue very often.

Buy – Don’t Hold by Leslie Masonson is called a investing book, but I’m tempted to put it in the trading category.Â It depends on how you prefer to define the difference between the two. The book’s subtitle is “Investing with ETFs using relative strength to increase returns with less risk”.Â Using relative strength makes me think trading, but there are definitely elements of the approach outlined in the book which speaks toward what I would probably think of as investing.Â In anyÂ case,Â as I noted in The Essentials of Trading, I look at trading and investing as being functionallyÂ the same thing, with perhaps a philosophical difference in approach.Â I’ll leave it to the reader to make their own judgement.

This book is largely a practical text focused on application. The author outlines a very specific strategy for deciding whether the stock market is to be considered in an uptrend, downtrend, ranging, or turning. His “dashboard” comprises a collection of indicators which are very much technical analysis oriented. They include market breadth indicators, sentiment readings, and some basic price studies. The scoring of the indicators provides the user a market reading from which to develop a strategy. From there, Masonson moves on to picking the best trading/investment vehicle based on relative strength readings. In other words, it’s very much a top-down approach.

On the plus side, the author is very good about explaining the various methods he employs in his strategy. He suggests specific tools (most free, some paid, but not necessarily required) and walks the reader through applying things. On the negative side, much of the first third of the book is dedicated to proving how bad an idea buy-and-hold investing is -Â definitely overkill there – and I thought in general the writing could have been better. Also, while Masonson does demonstrate the value of the dashboard indicators he uses, he doesn’t actually show a good historical look at how the overall strategy would have done. Still, it’s a book which can certainly provide the fodder for research and development for those interested in longer-term stock market trading/investing and/or asset allocation between and among markets.

First, a zero some game is one in which there must be an equalÂ loser for each winner. Basically, it’s a matched pair where there can never be any net gain or loss in value in the aggregate because increases in value for one side are offset by decrease in value on the other side.

Think of it like this. Billy and Bobby each have 5 balls for a total of 10. They are in an enclosed space, so no new balls can be introduced and no balls removed. In order for Billy to have 6 balls, one must be taken away from Bobby, who will be left with 4.

In trading terms, zero sum mean that there is a short for every long. The futures market is a perfect example of this. Futures are contracts for an exchange to take place at a later date. There are two sides to each contract – a long and a short. The long benefits from an increase in the value of the contract, and suffers from a decrease. It’s vice versa for the short, on a dollar for dollar basis. What the long gains comes from the losses of the short.

In asset markets, however, there isn’t necessarily a short on the other side of a long position. In fact, in most cases there isn’t. That means generally speaking, someone who owns the stock will be the sole winner or loser should the value of the stock change. No one else is mirroring that performance on the other side. It’s like owning a house. There’s no short on the other side of a home purchase, so the home owner is the only one impacted by changing values in the property.

I have heard some contend that the seller of the stock (or house) is in fact like a short because of the forgone gains or losses. That’s an opportunity cost argument, though, and one which really cannot be pursued in any reasonable fashion for the simple reason thatÂ we don’t know what the seller is doing with the funds, nor do we know if the buyer is actually making the best investment with her/his money.

Others might contend that if you only look at “trading” then stocks are zero sum. Again, since there doesn’t have to be a short on the other side of a stock long then it’s not really zero sum. Besides, traders buy stocks from investors and investors buy stocks from traders, so you cannot look at the groups in isolation.

I posted before about the NFA’s new rules on maximum forex trading leverage permissible for traders with US brokerage accounts (see New NFA Retail Forex Leverage Restrictions). Those went into effect on Monday. Tuesday new leverage rules kicked in for the trading in leveraged ETFs. Darwin’s Finance has a good write-up on the subject.

I find it somewhat interesting that margins on short ETFs is higher than on long ones. Granted, equities do tend to move more rapidly to the downside, but a double long ETF is going to move just as quickly as a double short when the market is falling (considering day time frame moves here, which is what the leveraged ETFs are intended to track). It’s basic math, so I see no real justification for the higher margin between the two.

The other interesting part of this is that even with the new margin requirements you can still trade at effectively 4:1 leverage. That’s a fair amount of leverage when you consider how much volatility there can be in the markets underlying these ETFs. Many experienced forex traders don’t go much beyond 10:1 leverage when they trade, and that’s in a lower volatility market (see Looking at Volatility Across Markets)

The other day I commented on a post on a personal finance blog. The article was an introduction to forex. I won’t link to it here because it was very poorly done, falling short on many points. One of the things that tripped off alarm bells early on about where the post was going was this statement:

However, it is important to note that forex trading is rather risky, and the currency market is quite volatile.

All trading is rather risky, so I won’t address that particular point. I will, however, speak to the issue of the currency market being quite volatile. Statements about the forex market being more volatile than others are made all the time – almost always by folks who are putting forex trading down in some fashion or another. As I’m going to show you, the numbers make it pretty clear that forex is in fact on the low end of the volatility scale when looking at all markets.

Here is a look at the last year worth of volatility in forex rates

Pair

Daily StdDev

Avg Daily Rng

EUR/USD

0.93%

1.41%

USD/JPY

0.91%

1.45%

GBP/USD

1.00%

1.65%

USD/CAD

1.02%

1.60%

The first column is the standard deviation (a commonly used volatility metric) of the daily % change for the one-year period beginning November 1, 2008. The second column is the average daily range, with each day’s range being expressed as a % of the prior day’s close ( [H-L]/C ). I went with % changes and ranges to make things directly comparable across markets. So from this data we can see that USD/CAD tends to see the biggest daily changes, though GBP/USD tends to have slightly wider daily ranges.

Now let’s compare that to the major US stock indices.

Index

Daily StdDev

Avg Daily Rng

Dow

2.01%

2.41%

S&P 500

2.26%

2.60%

NASDAQ 100

2.18%

2.69%

Russell 2000

2.89%

3.28%

Here we can see about what as we would expect in terms of the small cap Russell index being the most volatile in terms of both price changes and ranges.

And how about individual stocks?

Stock

Daily StdDev

Avg Daily Rng

IBM

2.18%

2.85%

GE

4.20%

5.59%

AAPL

2.66%

3.44%

GOOG

2.51%

3.33%

AMGN

2.33%

3.03%

XOM

5.95%

6.66%

JPM

2.23%

2.88%

KO

1.74%

2.45%

All of the above are clearly large-cap stocks which would generally be expected to show less volatility than mid- or small-cap stocks (as witnessed by the higher volatility in the Russell index). Even still, with the exception of KO, they are all much more volatile than the forex pairs.

So what about commodities?

Commodity

Daily StdDev

Avg Daily Rng

Gold

1.61%

2.38%

Oil

4.35%

6.01%

Nat Gas

4.91%

6.54%

Corn

2.70%

3.83%

Again, the commodities are clearly much more volatile on a day-to-day basis than are forex rates.

Now to add in a market that’s considered the least risky by many folks – interest rates.

Instrument

Daily StdDev

Avg Daily Rng

Eurodollar

0.05%

0.06%

2yr Treasury Note

0.13%

0.18%

10yr Treasury Note

0.63%

0.92%

30yr Treasury Bond

0.99%

1.50%

I’m using the futures for the prices above. Finally we have a market where volatility is lower than forex! As you can see, the shorter maturity instruments (Eurodollars are 3mo) are calm compared to the others we’ve looked at here. Bonds, though, are in line with the volatility readings we see for the forex pairs.

So the bottom line is that not only are forex prices NOT the most volatile, they are actually on the lower end of the spectrum when looking at available markets. The numbers demonstrate it pretty clearly, even in a 12-month period which has seen its fair share of volatile trading.

Now granted, the application of leverage in forex creates the opportunity for very high levels of volatility in one’s trading account – but that’s not the market’s fault. Traders don’t need to use leverage. You can trade forex without it.

A reader named Susan left this comment recently on the Some Not-So-Great Tips for Using Stop Orders post I wrote a while back. I think it does a great job of highlighting a situation – or at least a type of situation – which new traders find themselves in where stops are concerned.

I have a question, as a newbie to trading, and using things like stops, etc. We had purchased a stock that started to go upâ€¦ after it was in profit, we placed a stop order, for about .15 below the current trading price. Until our stop order, the stock was steadily (fairly quickly) headed upwardsâ€¦ but just in case we were not at the screen, we thought we would try a stop order.

I canâ€™t figure out if we did something wrong, or what happened. But this is my perception of what happened -â€¦ within seconds of my placed stop order, the stock price steadily dropped to my exact stop price, my shares sold, and then headed right back up to the previous high, to go on higher. All within 5 mins or less.

I am aware stock prices fluctuate, but to my eyes, it seemed my lower â€œsteal of a sale priceâ€ was noticed, somehow snatched up, and thing continued on upwards.

Prices can fluctuate, and I guess coincidences can happen. Or the more obvious answer may be that I didnâ€™t place the order correctly, or understand what was to happen once I did.

My understanding was that this price was to execute only if the stock (naturally) dropped.. not to sell at this price immediately (which would otherwise seem kinda MARKETâ€¦.).

I know this isnâ€™t the case, but it seemed as if someone could read our price, got the stock prices to go down, grabbed ours at a â€œdeal/stealâ€ and then got the stocks to start moving up again. But I canâ€™t grasp what did happen, likely because I have no experience, so likely a misunderstanding of stops altogether, or movement of stocks, in the least.

Any help in understanding this? Thanks so much for your time.

OK. We don’t know what stock Susan is talking about here, so we don’t have a proper frame of reference for the price movements likely to be seen. That said, when I read that she was using a stop 0.15 below the market I just about fell over. I think most experienced stock traders would agree that this isÂ probably way too close. A move like that for most stocks is little more than statistical noise. You’re almost guaranteed that it will get hit just as a result of normal price volatility created by the interaction of buy and sell orders hitting the market – or by news induced price swings.

Tightness of the stop aside, anyone who’s been in the markets for any length of time has seen at least one instance of their stop getting hit and the market basically turning right back around. It’s very annoying, of course, but if you need to expect it. All you can do is review the analysis you did in placing your stop there and see if that was the right decision given what you knew at the time.

There are, of course, situations where stops and other standing orders do get “run” by the market, where large players attempt to create price movement to trigger the execution of those orders. That really only happens when there are large numbers of stops all in a very obvious location, though. Chances are if you’re stop is hit it probably wasn’t any conscious act.

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